This dataset contains the data required to reproduce the analysis and the figures in the paper: Circulating miRNAome of avian influenza-infected ruddy turnstones (Arenaria interpres) (doi: 10.1111/jav.03404).
Article abstract:
MicroRNAs (miRNAs) are highly conserved small noncoding RNAs that regulate gene expression post-transcriptionally. Circulating miRNAs - miRNAs that have been released from cells and circulate in the bloodstream - are relatively stable and interesting molecules for wildlife research, where they may form a proxy for gene expression as a function of the animal’s state under a variety of environmental challenges. Aiming at providing initial baseline data on the circulating miRNAome in avian wildlife, we assessed the miRNA profiles of wild ruddy turnstones (Arenaria interpres) on their Australian non-breeding grounds. The ruddy turnstone is a long-distant migrant and a significant reservoir species for low pathogenic avian influenza virus (LPAIV). We therefore investigated both LPAIV-infected and uninfected individuals for their specific miRNA profiles to potentially elucidate the species’ molecular mechanisms underlying its response to LPAIV infection. De novo miRNA characterisation in the ruddy turnstone genome identified 161 conserved and two novel, bird-specific miRNAs, with liver-enriched miRNA-122 being the most abundant. Z chromosome-linked miR-2954-3p was significantly more abundant in serum from males (ZZ) than from females (ZW). Furthermore, we found a sex- and age-associated effect of LPAIV infection on miRNA abundance in serum samples, including one novel miRNA. This circulating miRNA signature may reflect sex- and age-specific differences in the host response, indicating that circulating miRNAs could serve as a valuable non-destructive analytical tool for enhancing our understanding of avian infections in a wildlife context and should be explored further.
The data analysis pipeline for processing the sequencing data is contained in the script 01_MicroRNA_Sequencing_Analysis.sh. This script utilizes raw sequencing reads, which have been deposited in the European Nucleotide Archive (ENA) under accession numbers ERR10462083-94 (project accession PRJEB47802), as input data. The pipeline includes steps for quality control, adapter trimming, read filtering, de novo microRNA discovery, and differential expression analysis. The script 02_Coding_Article_Figures.sh contains the code used to generate the figures in the article.
For mapping and quantification, the file 03_ain_miRNAome.fasta, which contains the mature mioRNA sequences from ruddy turnstones (Arenaria interpres), is required. 04_Fastqc_Sequence_Length_Distribution_Plot.tsv is required to create Figure 2. The file 05_FeatureCounts_output.tsv contains the feature counts used for differential expression analysis. Figure 4, Table 3 and 4 in the article, and Supplemental Information Figure S3 were generated based on the results from this pipeline. The files 06_eff.RTS.csv and 07_mcmc.RTS.csv were used to generate Figure 5, Supplemental Information Figure S4 and Table S8.
